European Genome-Phenome Archive

File Quality

File InformationEGAF00000149715

File Data

Base Coverage Distribution

This chart represents the base coverage distribution along the reference file. Y-axis represents the number of times a position in the reference file is covered. The x-axis represents the range of the values for the coverage.

Data is represented in a log scale to minimise the variability. A high peak in the beginning (low coverage) and a curve descending is expected.

798 205 555633 938 954387 442 129199 208 22290 019 73137 007 18714 222 9015 331 6052 039 428870 515439 595266 140186 358139 486110 06289 00670 70157 55248 87841 16135 72130 08826 67223 53720 57219 39216 56115 29413 70512 46611 53711 26510 2949 9149 2378 2367 0247 1446 9376 3026 1645 8146 0475 5625 3274 7694 7234 9484 7654 5934 2234 2893 9354 0813 5613 8633 4763 6833 4743 5053 2263 2373 0813 0182 9072 6752 5042 4502 5552 4612 3692 2652 1252 0531 9981 9721 8931 7871 9381 7651 7751 6301 6661 5731 6271 5381 4421 5701 4321 4241 4761 3961 4161 4061 3461 3501 3191 3141 2691 3161 3371 2461 2721 2791 2121 2081 2421 2941 2291 0791 0821 1851 0661 1711 1861 1061 0879979929711 0201 1479739421 0301 1331 0399489309181 0411 08188989689091090885079481883070471078277170374471985378378077973290082779577680171576874380376276468267564661666066764265461059557057253354950249950456849960859856065456852147653054050745650149445846243146143642446845642040544545249844043649641744343546542139944040639540643043442141540241940237738844039439441433733239435439738944835836436234937732229935131833234934732832844733334530329533132429426729230130633332430229432734831836431630029129726328326026024423828225924924223925021824822925222424023224926623122624222922219125424323623723721423221825522721121919418521420520318423219918219319519919916019119220417919116918923218816319417717417516515915617615717516716018121420817215318117717817619717817316014116113015514813414413517316013815415613218119414513518015217111712213813913313912315114514114012213513314512614811513313112711711012011213311413613412113313212413812715013414313214311711511411911812012586115113951191321131219611011610510496123103891071189510483761231011181421241449411687119134129122120119112127125111126118119122145137120157145116122931051238495102124939596100891019793967589688678132106868810095827970867587787776888982821079487909569698680857476827662831128075737383757479848172768558647667726266626265667662707381704580638466488476645170678782816667627562667368598582616859576471767649676167746471626458666360535258555850534358585647515963585248635549595560485639644543534556505185564257594548495853494559635151675264538052565067494350385245473333433941444148484444514956673641453845405040285136494350523954374138403941433234473843503449332831333839334440434436464242635648393231333633423731402761283445413936394440284139512933263628513136382641313534303829383426432932283540324631274419252939502928242129302527342827302233292744313050323634383631323632334338352026352844332623322027221927263530272727373427372030223738363728273525272930362332354129302434342733212827221420172727332927273524252221272319172230222627362230262229313127273032212825132423182116262031261318121513241920121220201617162126171915242119251524212926263128293240263024302324282318243335352120 608100200300400500600700800900>1000Coverage value1001k10k100k1M10M100M# Bases

Base Quality

The base quality distribution shows the Phred quality scores describing the probability that a nucleotide has been incorrectly assigned; e.g. an error in the sequencing. Specifically, Q=-log10(P), where Q is the Phred score and P is the probability the nucleotide is wrong. The larger the score, the more confident we are in the base call. Depending on the sequencing technology, we can expect to see different distributions, but we expect to see a distribution skewed towards larger (more confident) scores; typically around 40.

800 471150 339645 0751 385 0832 527 1111 033 07711 621 05215 181 1983 066 46421 098 12927 156 54913 151 2457 088 7943 513 9012 649 6701 712 255806 0155 049 75323 082 41527 268 72730 531 74118 195 50224 334 57513 392 68657 987 13813 800 12021 218 45315 861 27429 415 34245 123 97047 322 451113 958 909134 170 457181 040 952202 960 621584 117 1781 229 281 8601 721 259 443574 861 81795 391 76419 454 8371 735 27502 256 91200510152025303540Phred quality score0G0.2G0.4G0.6G0.8G1G1.2G1.4G1.6G# Bases

Mapped Reads

Number of reads successfully mapped (singletons & both mates) to the reference genome in the sample. Genetic variation, in particular structural variants, ensure that every sequenced sample is genetically different from the reference genome it was aligned to. Small differences against the reference are accepted, but, for more significant variation, the read can fail to be placed. Therefore, it is not expected that the mapped reads rate will hit 100%, but it is supposed to be high (usually >90%). Calculations are made taking into account the proportion of mapped reads against the total number of reads (mapped/mapped+unmapped).

93.8 %66 851 09893.8 %6.2 %

Both Mates Mapped

When working with paired-end sequencing, each DNA fragment is sequenced from both ends, creating two mates for each pair. This chart shows the fraction of reads in pairs where both of the mates successfully map to the reference genome. .

Notice that reads not mapped to the expected distance are also included as occurs with the proper pairs chart.

92.5 %65 926 77892.5 %7.5 %

Singletons

When working with paired-end sequencing, each DNA fragment is sequenced from both ends, creating two mates for each pair. If one mate in the pair successfully maps to the reference genome, but the other is unmapped, the mapped mate is a singleton. One way in which a singleton could occur would be if the sample has a large insertion compared with the reference genome; one mate can fall in sequence flanking the insertion and will be mapped, but the other falls in the inserted sequence and so cannot map to the reference genome. There are unlikely to many such structural variants in the sample, or sequencing errors that would cause a read not to be able to map. Consequently, the singleton rate is expected to be very low (<1%).

1.4 %924 3201.4 %98.6 %

Forward Strand

Fraction of reads mapped to the forward DNA strand. The general expectation is that the DNA library preparation step will generate DNA from the forward and reverse strands in equal amounts so after mapping the reads to the reference genome, approximately 50% of them will consequently map to the forward strand. Deviations from the 50%, may be due to problems with the library preparation step.

50 %35 644 40450 %50 %

Proper Pairs

A fragment consisting of two mates is called a proper pair if both mates map to the reference genome at the expected distance according to the reference genome. In particular, if the DNA library consists of fragments ~500 base pairs in length, and 100 base pair reads are sequenced from either end, the expectation would be that the two reads map to the reference genome separated by ~300 base pairs. If the sequenced sample contains large structural variants, e.g. a large insertion, where we expect the reads mapping with a large separation would be a signal for this variant, and the reads would not be considered as proper pairs. Based on the sequencing technology, there is also an expectation of the orientation of each read in the fragment.

The rate of proper pairs is expected to be well over 90%; even if the mapping rate itself is low as a result of bacterial contamination, for example.

81.2 %57 905 00081.2 %18.8 %

Duplicates

PCR duplicates are two (or more) reads that originate from the same DNA fragment. When sequencing data is analyzed, it is assumed that each observation (i.e. each read) is independent; an assumption that fails in the presence of duplicate reads. Typically, algorithms look for reads that map to the same genomic coordinate, and whose mates also map to identical genomic coordinates. It is important to note that as the sequencing depth increases, more reads are sampled from the DNA library, and consequently it is increasingly likely that duplicate reads will be sampled. As a result, the true duplicate rate is not independent of the depth, and they should both be considered when looking at the duplicate rate. Additionally, as the sequencing depth in increases, it is also increasingly likely that reads will map to the same location and be marked as duplicates, even when they are not. As such, as the sequencing depth approaches and surpasses the read length, the duplicate rate starts to become less indicative of problems.

10.2 %7 300 23710.2 %89.8 %

Mapping Quality Distribution

The mapping quality distribution shows the Phred quality scores describing the probability that a read does not map to the location that it has been assigned to (specifically, Q=-log10(P), where Q is the Phred score and P is the probability the read is in the wrong location). So the larger the score, the higher the quality of the mapping. Some scores have a specific meaning, e.g. a score of 0 means that the read could map equally to multiple places in the reference genome. The majority of reads should be well mapped, and so we expect to see this distribution heavily skewed to a significant value (typically around 60). It is not unusual to see some scores around zero. Reads originating from repetitive elements in the genome will plausibly map to multiple locations.

7 215 53616 67517 27936 31915 53520 78518 69624 26724 430139 99679 25036 528120 45546 32931 395253 33545 141251 45885 79016 226146 7205 97354 036373 4504 989105 5216 3514 9555 6262 839 3577 1265 9186 6327 7246 2328 566168 3508 276 04815 8348 78223 02219 99010 64440 55216 78822 578100 76034 04037 74441 33265 95629 19277 65855 57676 250114 790205 17249 763 149051015202530354045505560Phred quality score5M10M15M20M25M30M35M40M45M# Reads

Mapped vs Unmapped

Stacked column chart for both mapped and unmapped reads along all chromosomes in the reference file. It is a similar representation as shown in the Mapped reads chart but for each chromosome. Although sequenced sample may be a female, it is possible to get reads in the Y chromosome as there are common regions in both chromosomes called pseudoautosomal regions (PAR1, PAR2).

Unmapped reads belonging to each chromosome are determined when the one mate/pair is aligned and the other is not. The unmapped read should have chromosome and POS identical to its mate. It could also be due when aligning is performed with bwa as it concatenates all the reference sequences together, so if a read hangs off of one reference onto another, it will be given the right chromosome and position, but it also be classified as unmapped.

100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%100%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%0%123456789101112131415161718192021XYM0%10%20%30%40%50%60%70%80%90%100%mappedunmapped